{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jermwatt/machine_learning_refined/blob/main/notes/3_First_order_methods/A_5_Minibatch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "O51jFcDoLuHD"
   },
   "source": [
    "## Appendix A. Advanced First- and Second-Order Optimization Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains interactive content from an early draft of the university textbook <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main\">\n",
    "Machine Learning Refined (2nd edition) </a>.\n",
    "\n",
    "The final draft significantly expands on this content and is available for <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main/chapter_pdfs\"> download as a PDF here</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pjKBexIELuHE"
   },
   "source": [
    "# A.5 Mini-Batch Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nFSfMxC1LuHF"
   },
   "source": [
    "In machine learning applications we almost never tasked with minimizing a single mathematical function, but one that consist a *sum* of $P$ functions.  In other words the sort of function $g$ we very often need to minimize in machine learning applications takes the general form \n",
    "\n",
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}\\right) = \\sum_{p=1}^P g_p\\left(\\mathbf{w}\\right).\n",
    "\\end{equation}\n",
    "\n",
    "where $g_1,\\,g_2,\\,...,g_P$ are mathematical functions themselves.  In machine learning applications hese functions $g_1,\\,g_2,\\,...,g_P$ are almost always of the same type - e.g., they can be convex quadratic functions with different constants paramterized by the same weights $\\mathbf{w}$.  \n",
    "\n",
    "This special *summation structure* allows for a simple but very effective enhancement to virtually any local optimization scheme, and is called *mini-batch optimization*.  Mini-batch optimization is most often used in combination with a gradient-based step like any of those discussed in the prior Sections, which is why we discuss the subject in this Chapter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pgH7tNlFLuHG",
    "outputId": "676fbd17-b414-4536-b0bc-95acb21ccd1f"
   },
   "outputs": [],
   "source": [
    "# import standard libs\n",
    "import os\n",
    "\n",
    "# if on collab pull required subdirectories\n",
    "if os.getenv(\"COLAB_RELEASE_TAG\"): \n",
    "    # install github clone - allows for easy cloning of subdirectories\n",
    "    !pip install github-clone\n",
    "    from pathlib import Path \n",
    "\n",
    "    # clone library subdirectory\n",
    "    if not Path('chapter_3_library').is_dir():\n",
    "        !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/3_First_order_methods/chapter_3_library\n",
    "    else:\n",
    "        print('chapter_3_library already cloned!')\n",
    "\n",
    "    # clone images\n",
    "    if not Path('chapter_3_images').is_dir():\n",
    "        !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/3_First_order_methods/chapter_3_images\n",
    "    else:\n",
    "        print('chapter_3_images already cloned!')\n",
    "\n",
    "# append path for local library, data, and image import\n",
    "import sys\n",
    "sys.path.append('./chapter_3_library')\n",
    "sys.path.append('./chapter_3_images') \n",
    "\n",
    "# import section helper\n",
    "import section_3_11_helpers\n",
    "\n",
    "# image paths\n",
    "image_path_1 = 'chapter_3_images/batch_vs_miinbatch_functions.png'\n",
    "image_path_2 = 'chapter_3_images/minibatch_functions.png'\n",
    "\n",
    "# standard imports\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image, HTML\n",
    "\n",
    "# import autograd-wrapped numpy\n",
    "import autograd.numpy as np\n",
    "from autograd import value_and_grad \n",
    "from autograd.misc.flatten import flatten_func\n",
    "\n",
    "# this is needed to compensate for matplotlib notebook's tendancy to blow up images when plotted inline\n",
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.autolayout'] = True\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BVcnUBAbLuHH"
   },
   "source": [
    "## A simple idea with powerful consequences"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tnTwtGnJLuHH"
   },
   "source": [
    "Suppose we were to apply a local optimization scheme to minimize a function $g$ of the form\n",
    "\n",
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}\\right) = \\sum_{p=1}^P g_p\\left(\\mathbf{w}\\right).\n",
    "\\end{equation}\n",
    "\n",
    "\n",
    "where $g_1\\,g_2,\\,...,g_P$ are all functions of the same kind (e.g., quadratics with different constants parameterized by $\\mathbf{w}$).  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Xu_ZDDnHLuHH"
   },
   "source": [
    "The motivation for *mini-batch optimization* rests on a simple inquiry: for this sort of function $g$, what would happen if instead of taking one descent step in $g$ - that is, one descent step in the entire sum of the functions $g_1,\\,g_2,\\,...,g_P$ *simultaneously* - we took a sequence of $P$ descent steps in $g_1,\\,g_2,\\,...,g_P$ *sequentially* by first descending in $g_1$, then in $g_2$, etc., until finally we descend in $g_P$.  In other words, what would happen if we were to try to minimize $g$ by taking descent steps in the summand functions $g_1,\\,g_2,\\,...,g_P$ one-at-a-time?   As we will see empircaly throughout this text, starting with the examples below, in many instances this idea can actually lead to considerably faster optimization of a function $g$ consisting of a sum of $P$ functions as detailed in general above above.\n",
    "\n",
    " The gist of this idea is drawn graphically in the figure below for the case $P = 3$, where we compare the idea of taking a the a descent step simultaneously in $g_1,\\,g_2,\\,...,g_P$ versus a sequence of $P$ descent steps in $g_1$ then $g_2$ etc., up to $g_P$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 502
    },
    "id": "9KnWtXW-L56J",
    "outputId": "49717089-141f-4c8a-a941-9132b2a9618d"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": 1000
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_1, width=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7DFWCKowLuHI"
   },
   "source": [
    "Taking the first step of a local method, we begin at some initial point $\\mathbf{w}^0$, determine a descent direction $\\mathbf{d}^0$, and transition to a new point $\\mathbf{w}^1$ as \n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^1 = \\mathbf{w}^0 + \\alpha \\, \\mathbf{d}^0.\n",
    "\\end{equation}\n",
    "\n",
    "By analogy, if we were to follow the mini-batch idea detailed above this entails taking a sequence of $P$ steps, which we now describe.  If we call our initial point $\\mathbf{w}^{0,0} = \\mathbf{w}^0$, we then first determine a descent direction $\\mathbf{d}^{0,1}$ in $g_1$, the first function in the sum of $g$, and take a step in this direction as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^{0,1} = \\mathbf{w}^{0,0} + \\alpha \\, \\mathbf{d}^{0,1}.\n",
    "\\end{equation}\n",
    "\n",
    "Next we determine a descent direction $\\mathbf{d}^{0,2}$ in $g_2$, the second function in the sum for $g$, and take a step in this direction\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^{0,2} = \\mathbf{w}^{0,1} + \\alpha \\, \\mathbf{d}^{0,2}.\n",
    "\\end{equation}\n",
    "\n",
    "Continuing this pattern we take a sequence of $P$ steps, where $\\mathbf{d}^{0,p}$ is the descent direction found in $g_p$, that takes the following form\n",
    "\n",
    "\\begin{array}\n",
    "\\mathbf{w}^{0,1} = \\mathbf{w}^{0,0} + \\alpha \\, \\mathbf{d}^{0,1} \\\\\n",
    "\\mathbf{w}^{0,2} = \\mathbf{w}^{0,1} + \\alpha \\, \\mathbf{d}^{0,2} \\\\\n",
    "\\,\\,   \\,\\,\\,\\,\\,\\,   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\vdots \\\\\n",
    "\\mathbf{w}^{0,p} = \\mathbf{w}^{0,p-1} + \\alpha \\, \\mathbf{d}^{0,p} \\\\\n",
    "\\,\\,   \\,\\,\\,\\,\\,\\,   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\vdots \\\\\n",
    "\\mathbf{w}^{0,P} = \\mathbf{w}^{0,P-1} + \\alpha \\, \\mathbf{d}^{0,P} \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Jf4UYsG1LuHJ"
   },
   "source": [
    "This sequence of steps completes one sweep through the functions $g_1,\\,g_2,\\,...,g_P$, and is commonly referred to as an *epoch*. If we continued this pattern and took another sweep through each the $P$ functions we perform a second *epoch* of steps, and so on.  Below we compare the $k^{th}$ step of a standard descent method (left) to the $k^{th}$ *epoch* of this mini-batch idea (right).  \n",
    "\n",
    "\n",
    "\\begin{array} {r|r} \n",
    "\\text{full (batch) descent step}  & \\text{mini-batch epoch, batch-size = 1} \\\\\n",
    "\\hline\n",
    "  &  \\mathbf{w}^{k,1} = \\mathbf{w}^{k-1,0} + \\alpha \\, \\mathbf{d}^{k-1,1}   \\\\\n",
    "  &     \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "\\mathbf{w}^{k} = \\mathbf{w}^{k-1} + \\alpha \\, \\mathbf{d}^{k-1}   &  \\mathbf{w}^{k,p} = \\mathbf{w}^{k-1,p-1} + \\alpha \\, \\mathbf{d}^{k-1,p} \\\\\n",
    "  &       \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "  &  \\mathbf{w}^{k,P} = \\mathbf{w}^{k-1,P-1} + \\alpha \\, \\mathbf{d}^{k-1,P} \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "Tz5ZVgoELuHJ"
   },
   "source": [
    "When employed with gradient-based steps these steps take a very convinent form.  For example, noting that $\\nabla g\\left(\\mathbf{w}\\right) = \\nabla \\sum_{p=1}^P g_p\\left(\\mathbf{w}\\right)$ the $k^{th}$ standard gradient descent step in all $P$ summands can be written as\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^k = \\mathbf{w}^{k-1} - \\alpha \\nabla \\,\\sum_{p=1}^P g_p\\left(\\mathbf{w}^{k-1}\\right)\n",
    "\\end{equation}\n",
    "\n",
    "where here the descent direction $\\mathbf{d}^{k-1} = - \\nabla \\,\\sum_{p=1}^P g_p\\left(\\mathbf{w}^{k-1}\\right)$.  The gradient descent direction in just a single function $g_p$ at the $k^{th}$ epoch of a mini-batch run is likewise just *negative gradient of this function alone* $ \\mathbf{d}^{k-1,p} = - \\nabla  g_p\\left(\\mathbf{w}^{k-1,p}\\right)$, and so the step minibatch step $\\mathbf{w}^{k,p} = \\mathbf{w}^{k-1,p-1} + \\alpha \\, \\mathbf{d}^{k-1,p}$ is given by\n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{w}^{k,p} = \\mathbf{w}^{k-1,p-1} - \\alpha \\,\\nabla g_p\\left(\\mathbf{w}^{k-1,p}\\right).\n",
    "\\end{equation}\n",
    "\n",
    "The table above comparing a single descent step at the $k^{th}$ epoch of standard gradient descent to its analagous mini-batch epoch can then be written as follows below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "fRKbTexKLuHJ"
   },
   "source": [
    "\n",
    "\\begin{array} {r|r} \n",
    "\\text{full (batch) descent step}  & \\text{mini-batch epoch, batch-size = 1} \\\\\n",
    "\\hline\n",
    "  &  \\mathbf{w}^{k,1} = \\mathbf{w}^{k-1,0} - \\alpha \\,\\nabla g_1\\left(\\mathbf{w}^{k-1,1}\\right)   \\\\\n",
    "  &     \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "\\mathbf{w}^k = \\mathbf{w}^{k-1} - \\alpha \\,\\nabla\\sum_{p=1}^P  g_p\\left(\\mathbf{w}^{k-1}\\right)  &  \\mathbf{w}^{k,p} = \\mathbf{w}^{k-1,p-1} - \\alpha \\,\\nabla g_p\\left(\\mathbf{w}^{k-1,p}\\right) \\\\\n",
    "  &       \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "  &  \\mathbf{w}^{k,P} = \\mathbf{w}^{k-1,P-1} - \\alpha \\,\\nabla g_P\\left(\\mathbf{w}^{k-1,P}\\right)  \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CAI4Z_n1LuHK"
   },
   "source": [
    "##   Descending with larger mini-batch sizes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PVArqNPLLuHK"
   },
   "source": [
    "Instead of taking $P$ sequential steps in single functions $g_p$ (a mini-batch of *size $1$*) one-at-a-time, we can more general (with functions $g$ that take the form $g\\left(\\mathbf{w}\\right) = \\sum_{p=1}^P g_p\\left(\\mathbf{w}\\right)$) take fewer steps in one epoch, but take each step with respect to *several* of the functions $g_p$ e.g., two functions at-a-time, or three functions at-a-time, etc.,.  With this slight twist on the idea detailed above we take fewer steps per epoch but take each with respect to larger non-overlapping subsets of the functions $g_1,\\,g_2,\\,...,g_P$, but still sweep through each function exactly once per epoch. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RvGEWzsKLuHK"
   },
   "source": [
    "Choosing a general batch size we split up our listing of functions into $M$ subsets, where each subset has the same size with perhaps the exception of one (e.g., if $P = 5$ and we choose a batch size of $2$ then we will have two subsets of two functions with a final subset containing just one).  If we denote $\\Omega_{m}$ the set of indices of those summand functions $g_1,\\,g_2,\\,...,g_P$ in our $m^{th}$ mini-batch then during our $k^{th}$ epoch we take steps like those shown in the table below.  Here $\\mathbf{d}^{k-1,m}$ is the descent direction computed for the $m^{th}$ minibatch."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cfV-J_P0LuHK"
   },
   "source": [
    "\n",
    "\n",
    "\\begin{array} {r|r} \n",
    "\\text{full (batch) descent step}  & \\text{mini-batch epoch, batch-size = M} \\\\\n",
    "\\hline\n",
    "  &  \\mathbf{w}^{k,1} = \\mathbf{w}^{k-1,0} + \\alpha \\, \\mathbf{d}^{k-1,1}   \\\\\n",
    "  &     \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "\\mathbf{w}^{k} = \\mathbf{w}^{k-1} + \\alpha \\, \\mathbf{d}^{k-1}   &  \\mathbf{w}^{k,m} = \\mathbf{w}^{k-1,m-1} + \\alpha \\, \\mathbf{d}^{k-1,m} \\\\\n",
    "  &       \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\\\\n",
    "  &  \\mathbf{w}^{k,M} = \\mathbf{w}^{k-1,M-1} + \\alpha \\, \\mathbf{d}^{k-1,M} \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6ocgH3QmLuHK"
   },
   "source": [
    "\n",
    "The size of the subset used is called the *batch-size* of the proces e.g., in our description of the mini-batch optimization scheme above we used batch-size = $1$ (mini-batch optimization using a batch-size of $1$ is also often referred to as *stochastic optimization*).  What batch-size works best in practice - in terms of providing the greatest speed up in optimization - varies and is often problem dependent."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lh1bxgr0LuHK"
   },
   "source": [
    "Once again in the case of gradient-based methods a mini-batch step using a batch size greater than $1$ can be written out quite clearly, and just as easily implemented.  If we denote by $\\Omega_m$ the set of indices of our summand functions $g_1,\\,g_2,\\,...,g_P$ in the $m^{th}$ mini-batch , then during the $k^{th}$ epoch of our mini-batch optimization if we use the standard gradient method our descent direction is simply the negative gradient direction in the sum of these functions i.e., \n",
    "\n",
    "\\begin{equation}\n",
    "\\mathbf{d}^{k-1,m} = - \\nabla \\,\\sum_{p \\in \\Omega_m} g_p\\left(\\mathbf{w}^{k-1,m}\\right).\n",
    "\\end{equation}\n",
    "\n",
    "Our corresponding epoch of mini-batch steps with batch size $M$ looks as follows."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "id": "D7kXzQAiLuHL"
   },
   "source": [
    "\n",
    "\\begin{array} {r|r} \n",
    "\\text{full (batch) descent step}  & \\text{mini-batch epoch, batch-size = M} \\\\\n",
    "\\hline\n",
    "  &  \\mathbf{w}^{k,1} = \\mathbf{w}^{k-1,0} - \\alpha \\nabla \\,\\sum_{p \\in \\Omega_1} g_p\\left(\\mathbf{w}^{k-1,1}\\right)   \\\\\n",
    "  &     \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,   \\,\\,\\,\\,\\,\\,   \\,\\,\\,\\,\\,\\,   \\\\\n",
    "\\mathbf{w}^k = \\mathbf{w}^{k-1} - \\alpha \\,\\nabla\\sum_{p=1}^P g_p\\left(\\mathbf{w}^{k-1}\\right)  &  \\mathbf{w}^{k,m} = \\mathbf{w}^{k-1,m-1} - \\alpha \\nabla \\,\\sum_{p \\in \\Omega_m} g_p\\left(\\mathbf{w}^{k-1,m}\\right) \\\\\n",
    "  &       \\vdots   \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,     \\,\\,\\,\\,\\,\\,  \\,\\,\\,\\,\\,\\,   \\,\\,\\,\\,\\,\\,   \\\\\n",
    "  &  \\mathbf{w}^{k,M} = \\mathbf{w}^{k-1,M-1} - \\alpha \\nabla \\,\\sum_{p \\in \\Omega_M} g_p\\left(\\mathbf{w}^{k-1,M}\\right)   \\\\\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qgvp4w_ALuHL"
   },
   "source": [
    "## Mini-batch optimization general performance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "c673zd4SLuHL"
   },
   "source": [
    "Is the trade-off - taking more steps per epoch with a mini-batch approach as opposed a full descent step - worth the extra effort?  Typically *yes*.  Often in practice when minimizing machine learning functions an epoch of mini-batch steps like those detailed above will drastically outperform an analagous full descent step - often referred to as a *full batch* or simply a *batch* epoch in the context of mini-batch optimiztaion.  \n",
    "A prototypical comparison of a cost function history employing a batch and corresponding epochs of mini-batch optimization applied to the same hypothetical function $g$ with the same initialization $\\mathbf{w}^0$ is shown in the figure below.  Because we take far more steps with the mini-batch approach and because each $g_p$ takes the same form, each epoch of the mini-batch approach typically outperforms its full batch analog.  Even when taking into account that far more descent steps are taken during an epoch of mini-batch optimization the method often greatly outperforms its full batch analog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "XFw6siMzMCgf",
    "outputId": "299c1727-ddcc-48c1-9a22-03f6f8e87e23"
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "width": 1000
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_2, width=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hGivj51ZLuHL"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 1. </span>  Minimizing a sum of quadratic functions via gradient based mini-batch optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "c3Fi0sRELuHL"
   },
   "source": [
    "In this example we will compare a full batch and two mini-batch runs (using batch-size $1$ and $10$ respectively) employing the standard gradient descent method.  The function $g$ we minimize in these various runs is as sum of $P = 100$ single input convex quadratic functions $g_p(w) = a^{\\,}_p + b_pw + c_pw^2$.  In other words, our function $g$ takes the form\n",
    "\n",
    "\\begin{equation}\n",
    "g\\left(\\mathbf{w}\\right) = \\sum_{p=1}^P g_p(w) = \\sum_{p=1}^P\\left( a^{\\,}_p + b_pw + c_pw^2\\right)\n",
    "\\end{equation}\n",
    "\n",
    "All three runs use the same (random) initial point $w^0 = 0$ and a steplength / learning rate $\\alpha = 10^{0}$ and we take $2$ epochs of each method."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bEpMjPNNLuHM"
   },
   "source": [
    "Below we plot the cost function history plots associated with the full batch (shown in blue), mini-batch with batch-sizes equal to $10$ and $1$ (in magenta and black respectively).  In the left panel we show these three histories with respect to the batch-size = $1$ steps, that is we show the cost function value at every single step of the batch-size = $1$ method and plot the histories of our other mini-batch method every $10$ steps and full batch method every $100$ steps for visual comparison.  In the right panel we show all three histories only after each full epoch is complete.  From these plots can see clearly that both mini-batch approaches descended significantly faster than their full batch version."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "5YRUDhSVLuHM"
   },
   "outputs": [],
   "source": [
    "class Quad_Sum:\n",
    "    '''\n",
    "    A small tool for creating a convex quadratic function that is a sum of convex quadratics, using iter\n",
    "    to enable easy access to each of the quadratic functions / summands\n",
    "    '''\n",
    "    # function for creating constants of quadratic sum, here N is input dimension, P = number of summands\n",
    "    def create_quadratic_constants(self,N,P): \n",
    "        # create list of random matrices, one for each term\n",
    "        const_list = []\n",
    "        for i in range(P):\n",
    "            # generate constant\n",
    "            a = np.random.randn(1,1)\n",
    "\n",
    "            # generate b vector\n",
    "            b = np.random.randn(N,1)\n",
    "\n",
    "            # generate matrix\n",
    "            C = np.random.randn(N, N)\n",
    "            C = np.dot(C.T, C)\n",
    "            const_list.append([a,b,C]) \n",
    "\n",
    "        self.const_list = const_list\n",
    "        \n",
    "    # final sum of quadratics\n",
    "    def g(self,w,iter):\n",
    "        cost = 0\n",
    "        for i in iter:\n",
    "            # get quadratic\n",
    "            const = self.const_list[i]\n",
    "            a = const[0]\n",
    "            b = const[1]\n",
    "            C = const[2]\n",
    "            \n",
    "            # add to term\n",
    "            cost += (a + np.dot(b.T,w) + np.dot(np.dot(w.T,C),w))[0]\n",
    "        return cost/P\n",
    "    \n",
    "# Use the simple generator above to create an instance of the desired sum of convex quadratics\n",
    "N = 1       # input dimension\n",
    "P = 100     # number of convex quadratics / summands in function\n",
    "demo = Quad_Sum()\n",
    "demo.create_quadratic_constants(N,P)\n",
    "g = demo.g    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "td3m0gtJLuHM"
   },
   "outputs": [],
   "source": [
    "# minibatch gradient descent\n",
    "def gradient_descent(g, alpha, max_epochs, w, num_train, batch_size):        \n",
    "    # flatten the input function, create gradient based on flat function\n",
    "    g_flat, unflatten, w = flatten_func(g, w)\n",
    "    grad = value_and_grad(g_flat)\n",
    "\n",
    "    # record history\n",
    "    w_hist = [unflatten(w)]\n",
    "    train_hist = [g_flat(w,np.arange(num_train))]\n",
    "   \n",
    "    # how many mini-batches equal the entire dataset?\n",
    "    num_batches = int(np.ceil(np.divide(num_train, batch_size)))\n",
    "\n",
    "    # over the line\n",
    "    for k in range(max_epochs):                   \n",
    "        # loop over each minibatch\n",
    "        train_cost = 0\n",
    "        for b in range(num_batches):\n",
    "            # collect indices of current mini-batch\n",
    "            batch_inds = np.arange(b*batch_size, min((b+1)*batch_size, num_train))\n",
    "            \n",
    "            # plug in value into func and derivative\n",
    "            cost_eval,grad_eval = grad(w,batch_inds)\n",
    "            grad_eval.shape = np.shape(w)\n",
    "    \n",
    "            # take descent step with momentum\n",
    "            w = w - alpha*grad_eval\n",
    "        \n",
    "            # update training and validation cost\n",
    "            train_cost = g_flat(w,np.arange(num_train))\n",
    "\n",
    "            # record weight update, train and val costs\n",
    "            w_hist.append(unflatten(w))\n",
    "            train_hist.append(train_cost)\n",
    "\n",
    "    return w_hist,train_hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "QEhQXFkHLuHM"
   },
   "outputs": [],
   "source": [
    "### run full batch zero-order methods ###\n",
    "num_train = P\n",
    "batch_size = P\n",
    "alpha_choice = 10**(0)\n",
    "num_epochs = 2\n",
    "w = np.random.randn(N)\n",
    "\n",
    "# full batch run\n",
    "batch_weight_hist,batch_cost_hist = gradient_descent(g, alpha_choice, num_epochs, w, num_train, batch_size)\n",
    "\n",
    "# make stochastic run\n",
    "batch_size = 1\n",
    "minibatch_weight_hist, minibatch_cost_hist = gradient_descent(g, alpha_choice, num_epochs, w, num_train, batch_size)\n",
    "\n",
    "# make mini-batch run of size 10\n",
    "batch_size = 10\n",
    "minibatch_weight_hist_2, minibatch_cost_hist_2 = gradient_descent(g, alpha_choice, num_epochs, w, num_train, batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "id": "nmtlbHP4LuHM",
    "outputId": "e873c132-215d-4b59-ad5c-5731d3764d12"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot runs\n",
    "section_3_11_helpers.compare_runs(batch_cost_hist,minibatch_cost_hist,minibatch_cost_hist_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Hb9T5kp1LuHN"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 2. </span>  Minimizing a sum of quadratic functions via zero order mini-batch optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YPeCg2h9LuHN"
   },
   "source": [
    "In this example we will compare a full batch and two mini-batch runs (using batch-size $1$ and $10$ respectively) employing the zero order descent method *coordinate search* detailed in [Section 2.6](https://jermwatt.github.io/machine_learning_refined/notes/2_Zero_order_methods/2_6_Coordinate.html).  The function $g$ we minimize in these various runs is the same sum of random convex quadratics used in the previous Example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Bf8HBvzILuHN"
   },
   "source": [
    "Below we plot the cost function history plots associated with the full batch (shown in blue), mini-batch with batch-sizes equal to $10$ and $1$ (in magenta and black respectively).  In the left panel we show these three histories with respect to the batch-size = $1$ steps, that is we show the cost function value at every single step of the batch-size = $1$ method and plot the histories of our other mini-batch method every $10$ steps and full batch method every $100$ steps for visual comparison.  In the right panel we show all three histories only after each full epoch is complete.  In either case, we can see clearly that both mini-batch approaches descended significantly faster than their full batch version."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "KKvRFUGJLuHN"
   },
   "outputs": [],
   "source": [
    "# zero order optimizer - designed to loop over mini-batches of functions\n",
    "def coordinate_search(g,alpha_choice,max_its,w,num_train,batch_size):\n",
    "    # construct set of all coordinate directions\n",
    "    directions_plus = np.eye(np.size(w),np.size(w))\n",
    "    directions_minus = - np.eye(np.size(w),np.size(w))\n",
    "    directions = np.concatenate((directions_plus,directions_minus),axis=0)\n",
    "        \n",
    "    # run coordinate search\n",
    "    weight_history = []         # container for weight history\n",
    "    cost_history = []           # container for corresponding cost function history\n",
    "    alpha = 0\n",
    "    \n",
    "    # how many mini-batches equal the entire dataset?\n",
    "    num_batches = int(np.ceil(np.divide(num_train, batch_size)))\n",
    "\n",
    "    # over the line\n",
    "    for k in range(1,max_its + 1):                   \n",
    "        # loop over each minibatch\n",
    "        train_cost = 0\n",
    "        \n",
    "        # check if diminishing steplength rule used\n",
    "        if alpha_choice == 'diminishing':\n",
    "            alpha = 1/float(k)\n",
    "        else:\n",
    "            alpha = alpha_choice\n",
    "        \n",
    "        # range over mini-batches\n",
    "        for b in range(num_batches):\n",
    "            # record weights and cost evaluation\n",
    "            weight_history.append(w)\n",
    "            cost_history.append(g(w,np.arange(num_train)))\n",
    "        \n",
    "            # collect indices of current mini-batch\n",
    "            batch_inds = np.arange(b*batch_size, min((b+1)*batch_size, num_train))\n",
    "\n",
    "            ### pick best descent direction\n",
    "            # compute all new candidate points\n",
    "            w_candidates = w + alpha*directions\n",
    "\n",
    "            # evaluate all candidates\n",
    "            evals = np.array([g(w_val,batch_inds) for w_val in w_candidates])\n",
    "\n",
    "            # if we find a real descent direction take the step in its direction\n",
    "            ind = np.argmin(evals)\n",
    "            if g(w_candidates[ind],batch_inds) < g(w,batch_inds):\n",
    "                # pluck out best descent direction\n",
    "                d = directions[ind,:]\n",
    "\n",
    "                # take step\n",
    "                w = w + alpha*d\n",
    "        \n",
    "    # record weights and cost evaluation\n",
    "    weight_history.append(w)\n",
    "    cost_history.append(g(w,np.arange(num_train)))\n",
    "    return weight_history,cost_history\n",
    "\n",
    "### run full batch zero-order methods ###\n",
    "num_train = P\n",
    "batch_size = P\n",
    "alpha_choice = 10**(-2)\n",
    "num_epochs = 2\n",
    "batch_weight_hist,batch_cost_hist = coordinate_search(g,alpha_choice,num_epochs,w,num_train,batch_size)\n",
    "\n",
    "# make stochastic run\n",
    "batch_size = 1\n",
    "minibatch_weight_hist, minibatch_cost_hist = coordinate_search(g,alpha_choice,num_epochs,w,num_train,batch_size)\n",
    "\n",
    "# make mini-batch run of size 10\n",
    "batch_size = 10\n",
    "minibatch_weight_hist_2, minibatch_cost_hist_2 = coordinate_search(g,alpha_choice,num_epochs,w,num_train,batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "id": "AysxbkkSLuHN",
    "outputId": "d7552715-d7c2-4eaa-fc0e-662f435eebc3"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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aRgVjGHnwDGv3JnoNDmOMybQsQTbGGJOstXtP0DlPNA/mj2Ad7rrK64AH80fQOU80a/dYkmyMyTosQTbGGJOs+ZGRzM0pic6bm1OYH2UVe8aYrCPTtWh7DsPX385mx8Z19HqsS7jDMcaYLG/rvhO87FNrXPDrRZRZ9i9r76vDvktzAfBs/gjyHjpJsQuiiQZivFt0gr9x9yNC/B5MxrMHOALkAQqFORZjEso0CfKWQzAbeDGfsr5PV1i3jhxNm3NnkaKUuCDc0RljTNZ1DGGzz+N8q7eT76KruX6ucDT/GbYVj2DPxTAsfyQ5FE4InABO4v763o/7m4OkE+jkEuzUPieQdSbeT26CZQvu9/wlYDNQEngKuAEoEca4jPGVKRLkLYegXQzMjQF++BFWrwag55QPmNHzKcYcwpJkY4xJJ7lRSuJqjgE2dbuNTT/+CK0bctXugjRq9SbNclxDs/lC5Gmgkc/tas4r5lPgNEkn0Mkl2AmnHUnhc/zNPwVEEfqkPJDnRJL5k/ctQDtgrs+0dUAHoAkwBkuSTcaQKRLk2XjJMcDIkXDBBVChAowcydwnn2T2iRy0T24ldizH+LDdwZjAFSsYw5MHz/Bgfp/CiAYN4PdlrLr/flZNbMyS5i25dvko8h/ID9/jbm8Bu4EGnEuYq4JEuSQ0CvcdzEiU8xPntCTdx4CDAT4/uXXGEt7e9WCUzMwmfnLsa643P9nfc2NCIMMnyHsOw0txvcMHDtCoZi92t32JPYVzsHfR18Ru20aPSy9l6UnIH53IF3gfRP8J0VMhZhtE54eYVhBdDWIuib9swi++1cllPXZoz5jUufb0aZoczxH/RL1CheDLLyk98BWW9X+aatWWMnnyZKq3rQ5tvWV2AD/gEuYHgfVAHc4lzLWBnKF8J0kTziV+Gc0ZgpO0x93/F9ibwuckVTKTXFItwLJk3mMvYBVwIYn/Jgfy137Hs5f06vDK8AnyEeVc7dvJkxzZs4lqK0tQ9rsLKLStDatW72XVdZC/FMRcAScj3Zf+JHDiMJz8FU7shZMN4EQMnIx2txO74GQBbxrnvuj+vvRJfSED+dKmx/OjsWFIUsIO7RmTemUuiuH9PSeYfyKSQfkjzv6D+cS/yrWdH2fntQ24++67qVevHq+99hqPPPIIIgJFgDu9G8A+YAEuYe4DLAeqci5hrgfkC/W7yxwigFzeLSNJWDLjL6neDNyXzLoOAceBAySfqAf61zd5T2uyHYy/vvcjyPxlM+GS3h1eoqpBWE3K1ahRQwO5vOmew1An77naN1/5H+pLgxEraN7pIx74OTeRa3E9E42Ba4G/gM5JrHwUSR7LUdx/7P6S58T+pnZeap8fSfiS9+TWHUXG+uKPxiXD/iSzOxgTVCKyWFVrhDuOQNtiX/6upLd3717uv/9+ZsyYQcuWLRk1ahT58+dPemWHgZ85V5axGCjPuYS5AXBRisIzGdQe3E90Yr/nccrgdodg9QQm/B0PVtKd3N9Al40l+El3sNaV0X7DfSXW4RUnpR1e/triDJ8gA4w+BB0SOwnv77+hYkXu/N8rTO7Xy/3L+QMwD5iDS5CTenuBfhMzaMGq4k4oSe/kPbXrTuxkl3Al74eBO4BEL7juCXbDbLK2tDYLmTlBTkpsbCyvv/46Tz75JCVLlmTy5MnUqJGCt3kcWMi5hPln4DLOJcwNgWJBC9eEmHVUxJdY2UwoEvlAljlN+vSaB+PveFzFlj8p2Y8ydYIcbxSLBPLXa8BFu3ezdvVKdzgvziZcxnM6iRVHAWtx/fKJvjBWsJoGsZxL4MOdvB8FtgUQ86VAbpIvbUnP+77/vVsJTcYTrGYhpQmyiNwMDMUdlR2pqi8nmN8OeAXY6k0apqojk1tvsBPkOD/99BN33303O3bs4NVXX+XRRx+N30YH6jSwlHMJ8w+4HmXfkTJKkXG7ukw8wez5M+krlsB/Z0PdE38ymdhT0uGVqRNkODcO8sALzv0o9T0EBz4aS8+H2jF//nyuueaac08I5FiO4BrX64FrgFq47ATsW5zFBLI7lAI+AfLiPwkP5H5qn5fw/klckpweyXew7me3k19CcVjPz7IRwGpcHv4Pro+1jar+7bNMO6CGqnYNMAQg/RJkcCUX7dq1Y/r06dxxxx2MHj2aAgUKpG2lsbi65bgT/77D1Zr5JszlsIQ5A4v7J3MgPr/nWN+TCUwg/Z/RwBr893/6yvQJcpw9h+GoQm6BQnnh6NGjFCtWjFtvvZXx48fHXzi5Yzlv4rKi74D5uFNna+Lql48Ag5N4bnY7DpQFZLZDe74lNOmZiKcl4Y874z/cve3+7gd73Nhg7kMpTJDrAs+p6k3e474AqjrQZ5l2ZLAEGUBVz5ZcXHrppXz88cfUqlUriC+A+8/3e5/bv7hSjLiEuTLZ77+5TGAP7uhebqy0zQQu2LXsWSZBTkzXrl0ZOXIkW7du5aKLfM7mSGl3z0HgR+BrYAQuA/AnkK2fQWuXsys7KBBccSe/ZITedn/3z3AuaU5r8n0aGAfsT2KbBKNR9rNsK+BmVe3oPW4L1PZNhr0EeSBu5OHVQHdV3eJnfZ2ATgAlS5asvmlTUtX5wfHLL7/QunVrtm/fziuvvEK3bt1SV3IRiC2c62H+HldfVY9zCXMN3AdrjMmUQtFZEVCCnB61b8FMkP/44w8qV67Ma6+9Ro8ePeLPTM2xnE1AWVz3nT+RwO9AhUTmWe1yhmWH9rKXM7ivcTAS7l3Aa7gj/P4E47Cen2UDSZAvAg6r6gkR6Qy0VtUmya07vXuQfe3bt48HHniAadOm0aJFC0aPHs2FF16Y/i+8C9f5EZcwr8aV1MUlzHVw3ZjGmEwhQ4xikV61b8FulBs0aMDOnTtZtWoVOXIkcmpTSo7lBNJ/nxN3BlUFXP3yNbjhiA5j3ZSZgB3aMykVqsN6fpZNtsQiwfIRwD5VTWaMtdAmyOBKLt544w369OlD8eLFmTx5cnBLLgJxAPiJcwnz77gyjLiEuT6Q7JYzxoRTsDq8/LXFgZwkXwtYq6rrVfUkMAlonoLXDomHH36YtWvXMmfOnMQXKITbeoH8chXC9fgm5W3cJYheAwrg6plL4hrW5K6jGYg9uJ7sPQEub1IkJbuDMRBYs9CXdNunFgJlReRyEYkG7gam+S4gIkV9Ht4OrEifUNJGROjevTs//vgjAPXr12fIkCGEtNyvAHAL8DIuUd4NDMB1fLyGG86mGvA48Kk33xiToZTAlVH8jDty97P3OFh9kIEkyMVxiXqcf7xpCbUUkT9EZIqIJBqfiHQSkUUismj37uC2OC1btqRw4cK8++67wVnhDbge38Q08ebnxPU29MMlvqtJ+vgruH91kkp6t+CKa+rgyjzqeI8TrSQ0xoRSIM1CelDV00BXYBYu8Z2sqstF5AURud1brJuILBeR34FuuGNZGVbt2rVZunQpzZo1o0ePHrRo0YJ9+/aFJ5jcuA/wOeBbXOfH20BRXDFjWdzRwi7AR1h7bEwGkl4dXsEaZvVLoJSqVsKlimMTW0hVh6tqDVWtUbhw4SC9tBMTE0OHDh2YNm0aW7YEofUqgSuHGIU7bhrt/R2F/zKJuELFpKzFXd1vJG7UDN9Ok7iimg6447inOHct5HZYo2xMmKWmWQgWVZ2pqleqamlVfdGb9qyqTvPu91XViqpaWVUbq+rKdAwnKC688EI+++wz3njjDb766iuqVq3KL7/8Eu6w3AdbF3gCmIFLmCfgrvA3Fde7fAWuXR6F674Kz/nuxph0EkiCvJX47f6lnDsZDwBV3auqcWM+jASqBye8lOncuTOqyvDhw4OzwpT23+ch+bNz4sowvsN1NxUB7sSVaIwiOOUZxph0k96H9bIbEeGxxx5jwYIF5MiRg4YNG/L666+HtuQiORFAVeAxXIK8C5c418W1zY1xV/drjet5/pPkjyYaYzK0QBLkTFP7VqpUKZo1a8aIESM4efIka9eu5a233kp7Qxto/30gRYr9gR7Ah7iq8t9wFd2LcKNeJCW58ow4Vr9sTLqzOvbgqlmzJkuXLuW2226jZ8+eNG/ePHwlF8kRXG9yZ1zP8hZcLfMtwBLgv0BhXNv+Gu5XNKmrGhhjMpxkE+TMVvv28MMPs3PnTj777DP69OlDt27d+Pnnn0MXQEqLFC8D7gP+F8C6NwI7k5hv9cvGmEysQIECTJ06laFDh/L1119TtWrV0LbfqSXA5cD9nCu5+BO4B1iPO8RQELgJeBE3RvPxsERqjAlQlrhQiK/Y2FjKlClDnjx5+Pvvv4mNjaVNmzZ89NFHQX8tv1Iz9khKhpa7CneVqAbe3yLYVTCMyWRSMsxbegr1MG+BWrhwIa1bt2bLli0MHDiQHj16JD6EZ2axl/hjMa/AFSPGDS1XF3ede2NMSKVlmLdMJUeOHHTp0oW//voLgP/+97988sknbN++HYAjR46kfxCpKVIMdGi5fcAw3Dgi43BnVpcF2pD2+mUrzTDGZBA1a9ZkyZIl3H777fTu3ZvmzZuzd+/ecIeVehcRv+RiO/A07uS+/+E6OmoDvXGnvSd1yUZjTLrLcgkyQPv27YmJieHWW2/l5Zdf5vTp0wwfPpy1a9dSqFAhJkyYEJpAUlqkGEh5Rgzukql9cI3oHlwZxapk1p1U/bKVZhhjMqACBQowZcoU3nrrLb755huqVq3KTz/9FO6wgiMfcCNu/OXvce3zK7gLlLyFK7+rDDwKfALsCE+YxmRXWTJBLlSoED/88APDhw+nbNmyNG3alPfee48hQ4Zw/PhxBg8enLHOkI6TmjGkcuCS8IPJrHsdrpfiG+CQz3QbWs4Yk4GJCF27duWnn34iKiqKRo0a8corrxAbm8WGifAdV/8bXEnGCFyi/CHuaOGVQEfc0cON2NByxqSjLFeDnJiZM2fSrFkzAC6++GJ27drF/Pnzueaaa0Ly+qkS7EtjF8UNQbQEWIxraOvjEuL3k3jeKFx5SCDxHsENdWen9RuTLKtBTrmDBw/SsWNHpkyZwi233MLYsWMpVCibNDixwF+cq2H+HteJ0sjndhXuhEFjTMCyTQ1yYm6++WZKly4NwMSJEylYsCBvvvkmAMOHD2fMmDEADB48mM8//zxMUSYQ7EtjDwCG4MZfjrtKVCFcz0RS7Mp/xpgMIn/+/EyePJlhw4YxZ84cqlatyoIFC8IdVmjkACrhxpSajKthngNcizv572bgEqAVblz9ZcCZMMRpTBaRLXqQAT799FPmzp3LW2+9xVNPPcXgwYNZuHAh9evXJyoqivnz51OjRg2KFSvGhg0biIqKCllsQZGaUSw24ZLaU0msNwKXRN+O6x1O62saYwDrQU6rJUuWcNddd7Fx40YGDBhAnz59MvcoF8GwCTeEXFwP807ckcK4HubqQCb7aTMmvflri7NNguxr8+bNXHHFFVxyySVs27YNgOLFi7N1q7tA4EcffUSbNm3CEluapHR4uUBKMwrgkujluIHx6/vcZuFqlf0JtDzDmGzIEuS0O3jwIJ06dWLy5MncfPPNjBs3jsKFC4c7rIxjJ/GHlluLGykjLmGuDeQKW3TGZAjZusQioZIlS3LHHXewbds2rrvuOurVq8fWrVu55557uPLKKxkyZEjGPIkvOSkdXi6Q0ozXcFf72wsMxQ0vNwF3dnXnZJ4byJX/bGg5Y0wq5c+fn0mTJvHuu+8yb948qlatyg8//BDusDKOS4CWuLZ7Ka4TpTvufJG+uKv9NcD9DnxN/BO4jcnmsmWCDNCjRw8iIiLo3bs3vXv3JjIykh49evDYY4+xcOHCzHH1Jn9SUr8c6JX/cuJ6jfsAX+AujZ2cTbgTDRNjtcvGmCAQEbp06cLPP/9Mrly5aNy4MQMHDsx6o1wEQwGgGTAI14GyE3geV3YxCCiGK8PoDnyGdVyYbC1blljEOXjwIPnz5493//Dhw5QoUYIbbriByZMnhzW+kEmvK/8JUA53tb963q0M8A9Wu2yyPSuxCL5Dhw7RqVMnPv74Y2666SY+/PBDK7lIiRO4zo+4koyfgEuJP1JG8bBFZ0y6sBKLRMQlx7738+bNS6dOnZg6dSqbNm0KV2ihlV5X/nsPd4Lf1bjDd9cDFwO3kfar/oGVZxhj4rnggguYOHEi7733HvPnz6dKlSp8//334Q4r84jBHSnsC3yFK60bhxsWdDKutK408ADwAa6DJC19bNaGmwwsWyfI/nTt2hURYdiwYeEOJbSCfeW/prjDdY8CE3EN4bckf0Wol7Ch5YwxqSIidO7cmV9++YU8efLQuHFjXnzxRSu5SI1I4pdc7AKmAbVwFzNphOthbgO8izuZO5DNbG24yQQsQU5EiRIlaNWqFSNGjODw4cPhDifjSs2V//ID+5JZ7zqgLfAqsAA47jPPrvxnjAlAlSpVWLx4Ma1bt6Zfv340bdqUXbt2hTuszC0HUBF4CNfp8Q+uFONG3MnczXFHCe/Ajbu/GDidYB3WhptMwhJkP7p3787BgwfPXkTE+JHS8ow8uF7qpFwGtMD1OD8GXIQbjuhx4EWsPMMYE5B8+fIxYcIEhg8fznfffUeVKlX47rvvwh1W1iHEL7lYC/yOu2rrGuB+XPvdFHdk8EdgJsFpw41JZ5Yg+1G7dm3q1KnD0KFDOXPGLkeUrEDLMwKpXX4WN4TcW7gTRnYDrwAXYFf+M8akiIjw4IMP8uuvv5IvXz6aNGnCgAEDrF1PL8WBu4F3cJfGXodrz/fgrgL4UDLPD2R4UGNCwBLkJPTs2ZO1a9fyxRdfhDuUrCXQoeXi5MbVunUg6av+AawHPvL+Jjx5xA7tmUxORG4WkVUislZEnkxiuZYioiIS9lEyMorKlSuzaNEi7r77bp555hluvvlmdu7cGe6wsr5CuCOCr+OGCI1IZvmNwP70DcmYQFiCnIQ77riD0qVLM2jQoMx54ZCMKjW1yxBYecaFuEN0DYEiuJq4gcA83MklaT20Z6UZJkxEJAJ4G3fAugLQRkQqJLJcPlxx0q+hjTDjy5cvH+PHj2fEiBH8+OOPVKlShXnz5oU7rOwjD66ELik5cKNlVAe6ACNxZRsJa5mNSWeWICchIiKCXr168dtvv513daaDBw/y7LPPcuiQ/0sPLV26NPuNhBGo9BpabjDwJbAVV55xHy6ZfQI3mkZSkjq0Z6UZJvxqAWtVdb2qngQm4f4FTOh/uMs+HE9kXrYnInTs2JFff/2V/Pnzc/311/PCCy9YyUUoBNKGv4trh4fh/g38HleyUQA3lv5juFK7lQQ2YoYxqRRQgpydD+vdf//9FC5cmMGDB8ebPmTIEP73v/8xdOjQRJ+nqnTu3JlHH32UrDIIf7oI9tByvuUZJYA7cZfL/oTADu0llvBaaYbJGIoTf2/7hwSXbRCRakAJVZ2R1IpEpJOILBKRRbt37w5+pJlApUqVWLRoEffccw/9+/fnpptuspKLUAikDc8N1AW64cZhXgFsw53odykwHbgFd8SwMe4Kr5OBDaRtXGZjfCSbIGf3w3q5cuWiW7duzJgxg7/++guAI0eO8NZbbwEwdOhQjhw5ct7z5s2bx8KFCwEYNGhQ6ALO6tJSnpHcob0o4FrgCty4nkOBXwjeWddWnmHSkYjkwFV69kxuWVUdrqo1VLVGdr7SXN68eRk3bhyjRo1iwYIFVKlShblz/X3ZTVCktg2/ANc+9wY+xp1nsh540pv3EdAAKAzcDDyDq3nelh5vwmQHgfQgZ/vDeg8//DC5c+fm1VdfBWDUqFHs27ePQYMGsXfvXkaPHn3ec15++WWKFClCjx49mDp1KqtXrw512FlXepVnDMOdHDIDuAl3CK8TaT/r2sozTHBsJf5efqk3LU4+3HUr54vIRtyeNi0rHdFLDyJC+/bt+e233yhQoADXX389zz//vJVcpKfUtOGJuQjXVvcDPsd9G/4AHvbmvwdUwh1naQ4MwF3V1TopTCBUNckb0AoY6fO4LTAswTLVgKne/flADT/r6oSrDF1UsmRJzUwee+wxjYyM1PXr12vJkiW1fv36qqraoEEDLVmypJ48efLssosWLVJABw0apDt27NCcOXNqx44dwxW6ibNZVZto4nt6E29+QhtVNdLPc+Jukaq6JIivabIFYJEm0/5q/PYzEtdndjmu3+13oGISy/tti31v1atXD9l7zuj+/fdfbdu2rQLapEkT3b59e7hDMmkVq6obVHWyqvZW1caqeoGqllLVO1V1sKrOVdWDYYrPhJ2/tjjNJ+lll8N63bt3R1W59dZb2bx5M0888QQATz75JJs3b2bixIlnl3355ZfJnz8/Xbp04ZJLLqF9+/aMHTuWrVu3+lu9CYXUHNpLaWnG3bgrSC0AjuLKL2zkDBMEqnoaN5LsLFxV5mRVXS4iL4jI7eGNLmvImzcvY8eOZfTo0fz8889UqVKFb7/9NtxhmbQQoBTufJTBuHZ3P64n+XZcr3M/oBhQDtcFOBT4CdeGm+wrsaxZ4/dC1AVm+TzuC/T1eZwf99O90bsdx1X9JNlzkRl7Le69914FtEKFCnrmzBlVVY2NjdWrr7767LRVq1apiGjfvn3PPm/9+vUaERGhvXr1ClfoJqHdqrrJ+5ucUZr0t2SUqp5R1RWqOlZVH1b3b2AuVY1O5rllkohhs7fu0qoa5f0dpdbrnEWQwh7k9LplxrY4FP766y8tX768iog+++yzevr06XCHZNLTKVX9XVVHqmoXVa2urg2vpKodVPVdVV2kqifCFaBJL/7aYjuslwK///67RkVF6UcffRRv+vjx4xXQL774Qjt27KgxMTG6Y8eOeMvcc889mjdvXt23b18oQzbBkNoyiZWqGuHneXG3KHVlHMF6TZNpWIKc8R0+fFjvv/9+BfTaa6/Vbdu2hTskE0rHVfU3VX1bVR9Q1atVNbeq1lTXETJaVf9UVfvfKVPz1xYnW2KhdljvrEqVKrF7927atGkTb3rr1q0pVaoUTz/9NOPGjaN9+/Zccskl8ZZ58sknOXz4MO+8804oQzbBkNqzri/CHdpLSixuQPxbgOdwJwjuIjilGWDlGcakQZ48eRgzZgxjxozht99+o0qVKsyeHeiXz2R6MUBN3El/o4E/ce3z67jfgDnAf3FjNDcEeuBG01iDDTeXBYhLnkOvRo0ampXGB3777bfp2rUrOXLkYM2aNVxxxRXnLXPrrbfy22+/sXHjRnLmzMmvv/5KnTp1EJEwRGxSZQ+uLi03gY3dPBo3XrI/o3BnYf8GLPT5e5SkrxxVBnfmt78YtuCS6JeAzbixpp/CjTGa0jPFTboQkcWqGvYRJrJaW5xe/v77b+68805WrFjB008/Tf/+/YmMjAx3WCYjOAAsxrXdi7y/h3CdHzWBGt7fEriaaJOh+GuLLUEOkqNHj1K2bFmuu+46xo0bl+gyP/74Iw0bNmTo0KHExMTQpUsXPvnkE1q1ahXiaE3IxF1kJLHe4CYk3gO9AbiSpBPkSGC5t1wwXtOEnCXImc+RI0d49NFH+eCDD7jmmmv46KOPKFasWLjDMhnRLrwxu3AJ80Jcr3Jcshz39xJ/KzChYglyCOzfv5/cuXMTExPjd5lrrrmGdevWERkZyaZNm6hUqRJLly4lRw676neWFdebO5Bzvbl98d+buwc3gu26JNYZgxvF/EpcIxvX4P4HdxnW5Hqt2ycT8x7gCG4Uj0CvcmhSxBLkzGvcuHE89NBD5MmTh/Hjx3PjjTeGOyST0SluxAzfXuZFuDbWtw2vgbtCoAkZf22xZWVBdOGFFyaZHAP069ePrVu3smnTJu655x7++OMPpk2bBsDy5cvZv39/KEI1oZTSQfEDuajJO8A+4H2gCm5Iov/D1cI97PdZTlIXNrGLmhiTrP/7v/9j0aJFXHzxxdx8883069eP06eTOuRjsj3BXdrnDuBF4BtgL25Yg7u8+wNwHShlcFdzfR34Hjgc+nCN9SCHnKrSsGFDTp48yYIFCyhfvjz58+dn+vTplC5dmuuvv/5swmyysdSWSfyNu3JUUhcBiwJW4calCcZrmlSxHuTM7+jRo3Tr1o1Ro0bRsGFDJk6cSPHixcMdlsnMzuDaZ9+e5j9xJ3z79jRXBnKGJ8SsxnqQMwgRYdasWcybN4+oqCieeuoplixZQvPmzTl27Bhffvkl9mNlUj1yxsUkP3KG4pLoRrizrifgGuRZ2MgZxqRA7ty5GTlyJB9++CFLliyhSpUqzJo1K9xhmcwsAqgA3A+8BfyCOwlwPFAPN9BuF6Ag7hrGnYGRwDLgVMijzdKsBznMTp06RdmyZdm0aRP//e9/mT9/PnXr1mX69OnhDs1kFOkxckYLYAnuzOu4XorNJD00kY2cEVTWg5y1rFy5kjvvvJO//vqLvn378sILL9goFyb9HMMly74nAW7CdX749jRfhXWFJsN6kDOoqKgonn/+eXLlysXAgQPp2bMnM2bMYOHCheEOzWQUhXDJZqAny92AK4lITBNvfkHgeuAJ4BPgO1zPRVI2AH+QePlGXHlGB9zJhae8vx286VbDbLK4cuXK8euvv9KxY0cGDhxI48aN+eeff8IdlsmqcuHOEekKjMWV1+0AXgYuw42pfyvuvJRrgd7AZNxl32yM5oBYD3IGcfToUXLnzs2///5LqVKlqFOnDjNmzAh3WCazSo+RM/IAhb1lq+DG+Kzm/f0ZeDCJ5wYyckZcHNlk9AzrQc66JkyYQOfOncmZMycffvghTZs2DXdIJrvaR/zh5hbhjkgmHG4uG5fOWw9yBpc7d24A8uXLR69evZg5cya//vprQM/dtWsXH3zwAarKxo0b+fjjj9MzVJMZpMfIGW/iepE34676VxyYCdwGdErmuUmNnAE2eobJUu69914WL15MsWLFuOWWW+jbt6+NcmHCoyBwI659/wzXpv6F63mOAIbjOjyKAbcD/wO+ws4hwXqQM6R///2Xyy+/nFq1ajFz5sxkl7/vvvuYMGECX3zxBUOHDmXu3Ln8+uuv1KpVKwTRmiwjtaNYbMLVJyf1+x+Ba5xv4Pwzr7Pp6BnWg5z1HTt2jMcff5zhw4dTv359Jk6cSIkSWXBnNpmb4jo+fEfOWIwrz/CtZ64O5A9PiOnJepAzkXz58tG7d2+++uorfvnllySXXb58OR999BEAnTt3Zu5cl2X069cv3eM0WUxqR87Ig6t5S0puXIlHQdzwRA/geqR/BKaR9tEzbOQMkwHlypWL999/n48++ojff/+dqlWrBtTpYUxICa4Nb4WrYf4WV5rxDe6E7u3As7ijhlcB9wFDgQW4co0syhLkDOqRRx6hUKFCPPfcc+fNGzt2LBMnTgTg2WefJW/evAwdOpQdO3ZQrFgxBgwYwOzZs/nuu+84cuQIjz/+OJs3bw7xOzCZUkpLMyCw8ow3cIf19uES7nrACuAx4NFknmsXNjGZXJs2bVi8eDGXXnopzZo144knnuDUKRuTy2RgcVdqvRcYguvMOABMAa7DDQ36OK79r4Q7Ifs9XA/0yZBHmz5UNSy36tWrq0naK6+8ooB+//33Z6dt3LhRo6OjNXfu3DpjxgwFtH///nr69Gm96667dPLkyXr06FEtWrSoNmjQQF988UUFtHXr1mF8JybL26yqTTTxb3sTb35iNqpqpJ/nxd1yqOpwb9nYILxmBgEs0jC1v743a4tD5+jRo9q5c2cFtF69erp5cwbfSY1JznFVXaiq76pqe1X9j6rmUtUaqvqQqo5W1T9U9VS4Akyev7bYapAzsGPHjlGmTBkuv/xyfvjhB0SE9u3bM2HCBM6cOUNERAR58+Zl/fr15M8fvzDonXfe4ZFHHiE6OpqoqCiOHDnCkiVLqFq1apjejcnyUjpyBgQ2esaFuNEy/gZO4E4oqQIcwg2Q708GHznDapCzr0mTJvHggw8SHR3N2LFjufXWW8MdkjHBcxRYSvyRM7biyut8a5rLEJw6hjS24VaDnAnlypWLZ599lgULFjBz5kxWrlzJ2LFjeeSRR2jXrh0nT56kT58+5yXHAB07duSyyy7j5MmTzJw5kwsvvPBsXfJDDz3Ec889R2xsLPfddx8jRowI9VszWVF6lWe8CswBtuGS5N64MUAnJvM8GznDZFB33303S5YsoWTJktx222306dPHSi5M1pEbqI8roRsPrAT+AV4AiuJO2L4Jd07KdcCTuNKNTaRsjOb0bsMT61YOxc0O6wXm5MmTWrp0aa1UqZK2bNlS8+bNq7t27dIdO3bo008/rUeOHPH73O+++07fe+89VVUdNGiQAjpgwAAFNCIiQl944QUFNE+ePLpjx45QvSVj4ktNqcRGVY3y8xzf222qOlBVv1LV7Wl8zYR2e3HsDvSNxoeVWGR7x44d04cfflgBrVu3rm7atCncIRkTOrtUdaaqvqCurS6iqoVVtamqPquq0zR+u+0riCV2/tpia5QzgQkTJqj3f5U+++yzqVrHkSNHtGjRogpo0aJFNU+ePAroFVdcoREREfrII4+oqmpsbGySSbcx6WKzqo5S1TKqGu39HaX+G7ndqlpak25lSqjqO6raU1WvU9WLVPUSVb1JXQOc1HNHBRBraXVJeulkYvUjNQkycDPu9Ji1wJOJzO8C/Aksw51WUyG5dVpbHH4ff/yx5suXTy+88EKdNm1auMMxJnz+UdXPVfVpVb1RVQuq6qWq2kJVX1TVWaq6V12bm9o2PAFLkDOxM2fOaKVKlfSiiy7SgwcPpno97777rgL6/vvv6zPPPKOATps2TTt37qyRkZG6du1a7datmxYpUkT37NkTxHdgTIB2q+omDaxXNqUNZKyqblHVCeoa3aSee7mfGELQa+HvhhtNeh1wBW4Qvt8TJsDABT73bwe+Tm691hZnDGvWrNGqVasqoD169NATJ06EOyRjwi9WVdep6seq2ktVr1XVfJr8yd1lNOCje2lKkK3XIvy2bNmiK1asSNM6zpw5o3PnztUzZ87oiRMndP78+aqqunXrVs2VK5c2atRIc+TIoYB27949GGEbk37SMnJGIOUZJdT1WvRX1U/VNdIjknlOEHot/N2AusAsn8d9gb5JLN8G+Cq59VpbnHEcO3ZMH3nkEQW0du3aunHjxnCHZEzGs16TT5Cj1XW2BMBfW5zsSXoiEgG8DTQFKgBtRKRCgsU+Uje4RxVgMPB6cus1KXPppZdSrly5NK0jR44cNG7cmBw5chAdHc0111wDQLFixejevTvff/89efLkoWXLlgwbNox165IaWsCYMEvLhU1KJrPu0sAnwD24KwSOBhoBnZN5XnInBqZNceKffvKPNy0eEXlERNbh2uJuia1IRDqJyCIRWbR79+50CdakXM6cORk2bBiffPIJK1asoEqVKnzxxRfhDsuYjCUfyV+cqiTuZME0CGQUi1rAWi9nPwlMApr7LqCqh3we5iFl5yGaDKBPnz6UL1+el156ibfeeouoqCieeiq54QWMCbP0GjnjKaA2cCcwAPgSd9Wo5FrMzYT9ylKq+raqlgaeABK9pKa6kaVrqGqNwoULhzZAk6xWrVqxZMkSrrjiClq0aEGPHj04eTKrXH3BmDQKpA3vS5qH7QwkQbZei2wgf/78LF++nK5du1K0aFF69+7N5MmTk73UtTEZQiFcj0GgDeINQBM/85p48xMK5JLaQei1SMJW4qf+l3rT/JmEu1CsyYRKly7NTz/9xKOPPsqQIUNo2LAhGzduDHdYxmQMqWnDUyho4yBbr0XmJyJn7/fq1YsiRYrQq1evuHpGY7KO1JRnhKjXIgkLgbIicrmIRAN3A9N8FxCRsj4Pm+H61U0mFRMTw5tvvsmUKVNYuXIlVatW5fPPPw93WMaEX2pL7FIgkATZei2yobx58/LCCy+wYMECPvvss3CHY0zwpaY8IwS9Fv6o6mmgKzALWAFMVtXlIvKCiNzuLdZVRJaLyDKgB3B/+kVkQqVly5YsXbqUMmXKcMcdd/D4449byYUxqWnDUyDZS02LSCSwGne9k624Xox7VHW5zzJlVXWNd/82oL8mcwlVu7xpxnf69GkqV67MqVOnWL58OVFRUeEOyZjwS80ltRNhl5o2KXXixAn69OnDm2++Sc2aNfn444+5/PLLwx2WMZlaqi81bb0W2VdkZCSvvPIKa9as4e233w53OMZkDOnca2GMPzExMQwdOpSpU6eyevVqqlatakf4jEknyfYgpxfrtcgcVJWmTZvyyy+/sGbNGqx23JjgsB5kkxYbNmygdevWLFy4kG7dujF48GBiYmLCHZYxmU6qe5BN9iYiDBkyhCNHjtCvnzv38uWXX2bSpElhjswYY7Kvyy+/nB9//JHHH3+cN998k/r167N+/fpwh2VMlmEJsklW+fLl6dq1KyNGjGDIkCH07duX9u3bs2nTpnCHZowx2VZ0dDRDhgzhs88+Y926dVStWpWpU6eGOyxjsgRLkE1A+vfvz0UXXUSPHj0oUaIEIkL37t3PW+748eNs3ZrUICfGGGOCqUWLFixdupRy5crRqlUrHn30UU6cOBHusIzJ1CxBNgEpUKAAL7/8MgBvvvkmzzzzDJ999hlfffXV2WVUlRYtWlCuXDm2bNnib1XGGGOCrFSpUvzwww90796dYcOGUb9+fdatWxfusIzJtCxBNgHr0KED27dvP3vp0yuvvJJu3bqd7amYMmUKs2bN4vDhwzz++OPhDdYYY7KZ6OhoXn/9dT7//HPWrVtHtWrVmDJlSrjDMiZTsgTZpEiRIkUA1xC/9dZbrF27lldffZV///2X7t27U6VKFV544QU+/fRTZs6cGeZojTEm+2nevDnLli2jfPny3HnnnXTt2pXjx4+HOyxjMhVLkE2q3XjjjbRq1YoXX3yRLl26sHXrVt555x2eeOIJypUrR9euXTl69Gi4wzTGmGznsssu4/vvv6dnz568/fbb1KtXj7Vr14Y7LGMyDUuQTZq8/vrriAgfffQRHTp0oG7dukRHR/POO++wYcMGXnrppXCHaIwx2VJ0dDSvvvoq06ZNY+PGjVSrVo3JkyeHOyxjMgVLkE2alChRgldeeYWrrrrq7El8AI0bN+a+++5j8ODBrFq1KowRGmNM9nbbbbexbNkyKlasSOvWrXn44Yet5MKYZFiCbNLs4YcfZsWKFRQqVCje9FdffZU8efLw8MMPE64rNhpjjIGSJUvy/fff07t3b959913q1q3LmjVrwh2WMRmWJcgmKETkvGmXXHIJL730EnPnzuXDDz8MQ1TGGGPiREVFMXjwYKZPn87mzZupVq2aXRXVGD8sQTbpqnPnztSvX5/HH3+cHTt2hDscY4zJ9po1a8ayZcuoVKkSbdq0oUuXLhw7dizcYRmToViCbNJVjhw5GDVqFEePHrVSC2OMySBKlCjB/Pnz6dOnD++//z5169Zl9erV4Q7LmAzDEmST7q666ipeeOEFPvvsMxu03hhjMoioqCgGDRrEjBkz+Oeff6hevToTJ04Md1jGZAiWIJuQ6NGjBzVq1OCRRx5h9+7d4Q7HGGOM55ZbbmHp0qVUrlyZe+65h86dO1vJhcn2LEE2IREZGcno0aM5cOAAjz32WLjDMcYY46NEiRLMmzePJ598kuHDh1OnTh0botNka5Ygm5D5z3/+Q79+/Zg4cSJffPFFuMMxxhjjIyoqioEDBzJz5ky2bt1K9erVmTBhQrjDMiYsLEE2IfXkk09SuXJlOnXqxK5du8IdjjGZhojcLCKrRGStiDyZyPweIvK3iPwhIt+KyGXhiNNkfk2bNmXZsmVUrVqV++67jwcffNBKLky2E1CCbA2zCZbo6GjGjx/PwYMHad++vY1qYUwARCQCeBtoClQA2ohIhQSLLQVqqGolYAowOLRRmqzk0ksvZd68efTt25eRI0dSu3ZtVq5cGe6wjAmZZBNka5hNsF199dVnz5x+//33wx2OMZlBLWCtqq5X1ZPAJKC57wKqOk9Vj3oPfwEuDXGMJouJjIzkpZde4quvvmL79u3UqFGD8ePHhzssY0IikB5ka5hN0D366KPceOON9OjRI829Evv27WPJkiVBisyYDKk4sMXn8T/eNH86AF/5mykinURkkYgsslFlTHJuvvlmli1bRrVq1Wjbti0dO3bk6NGjyT/RmEwskAQ5aA2zNcomTo4cORgzZgy5c+fm3nvv5eTJk6laz8mTJ7npppuoWbMmP/zwQ5CjNCbzEZH7gBrAK/6WUdXhqlpDVWsULlw4dMGZTKt48eLMnTuXp59+mtGjR1O7dm1WrFgR7rCMSTdBPUkvuYbZGmXjq2jRoowcOZIlS5bQv3//8+Zv2rQp2Ss79evXj0WLFnHRRRfRpk0b9uzZk17hGhNOW4ESPo8v9abFIyLXA08Dt6vqiRDFZrKJyMhIBgwYwNdff83OnTupUaMG48aNC3dYxqSLQBJka5hNumnRogUdO3Zk0KBBzJ49++z0nTt3UqdOHWrVqsW6desSfe706dN55ZVX6Ny5M7NmzWL37t20a9eO2NjYUIVvTKgsBMqKyOUiEg3cDUzzXUBEqgLv49pgGyLGpJsbb7yRZcuWUbNmTe6//37at29vJRcmywkkQbaG2aSroUOHUqFCBe699162bdvGmTNnuPfeezlw4AAiwp133snx48fjPWfjxo383//9H1WqVGHIkCFUrVqV119/nRkzZjBkyJAwvRNj0oeqnga6ArOAFcBkVV0uIi+IyO3eYq8AeYFPRGSZiEzzszpj0qxYsWLMmTOHZ555hjFjxlCrVi3+/vvvcIdlTNBIIMNsicgtwBtABDBaVV8UkReARao6TUTmAP8BtntP2ayqtye+NqdGjRq6aNGiNAVvso6///6bmjVrUqNGDa655hr+97//MXLkSC6++GJuv/12OnXqdHbEixMnTtCwYUNWrVrF4sWLKVOmDACqSqtWrZg2bRo//PADderUCedbMiZJIrJYVWuEOw5ri01azZkzh3vvvZfDhw/zzjvvcP/994c7JGMC5rctVtWw3KpXr67G+Bo3bpwCCmjbtm01NjZWVVWfeOIJBXTcuHGqqvrII48ooJ9++ul569i/f7+WKlVKL7vsMt27d29I4zcmJXAdDGFrg+Nu1habYNi2bZtee+21Cmi7du308OHD4Q7JmID4a4vtSnomw2jbti3du3enXr16vPvuu4gIAAMGDKBRo0Z06dKFF154gbfffpuePXtyxx13nLeOAgUKMGnSJLZt20abNm04c+ZMqN+GMcZkO0WLFmXOnDn079+fsWPHUqtWLZYvXx7usIxJNUuQTYby+uuvs2DBAvLkyXN2WmRkJJMmTSJfvnz079+f+vXrM3DgQL/rqF27Nm+//TbffPMNTz31VCjCNsaYbC8iIoLnnnuO2bNns3fvXmrWrMkHH3xgV0w1mZIlyCZTKFq0KFOmTKFp06ZMmjSJqKioJJd/8MEHeeihhxg8eDATJ04MUZTGGGOuu+46li1bRt26dWnfvj33338/hw8fDndYxqSIJcgm02jQoAEzZ87k0ksDu1DjG2+8QcOGDenQoQNLly5N5+iMMcbEKVKkCN988w3PPfcc48ePp2bNmvz111/xltmzZw+bNm2y8etNhmQJssmyoqOjmTJlCoUKFaJFixbs2mUjEBpjTKhERETQv39/5syZw/79+6lVqxajRo1i8+bNjB49mjp16lC2bFnq1KnD6NGj2bJlS/IrNSZELEE2WdrFF1/MZ599xq5du2jZsuV54ykbY4xJX02aNGHZsmXUq1ePjh07UqtWLTp06MC6des4deoU69ato0OHDrRr186SZJNhWIJssrzq1aszbtw4fvzxx7NX2tu5cydfffVVuEMzxphsoUiRIsyaNYsWLVqwc+fORJeZO3duvCuqGhNOliCbbOHOO+9k8ODBfPzxxzz22GM0btyYW265xa66Z4wxIbJ//37+/PPPJJcZOHCg1SSbDCEy3AEYEyq9evVi/fr1DBs2jOjoaBo1akSPHj0oVKgQbdu2DXd4xhiTpR05coTNmzcnucy6devo1asXderU4eqrr6ZixYpceOGFIYrQmHMsQTbZhojw1ltvccEFF9CgQQNuvPFGbrnlFh544AEKFixIs2bNwh2iMcZkWXny5KFkyZKsW7fO7zIxMTFMnTqVsWPHnp1WrFixs8ly3N8KFSqQL1++UIRtsikJ1wDeNWrU0EWLFoXltY2Jc+jQIRo3bsyKFSuYM2cO9erVC3dIJpsQkcWqWiPccVhbbEJp9OjRdOjQwe/8UaNG8cADD7BlyxaWL1/OX3/9dfbv33//zbFjx84ue9lll3H11VfHS57LlStHrly5QvFWTBbhry22HmSTrV1wwQV89dVX1K9fn2bNmvHdd99RqVKlcIdljDFZ0g033ECTJk2YO3fuefOaNGnCDTfcgIhQsmRJSpYsSdOmTc/OP3PmDBs3boyXNC9fvpzZs2dz8uRJAHLkyEHp0qXPJsxxyfOVV15JdHR0yN6nyfysB9kYYMOGDTRs2JDjx48zZ84cqlSp4nfZffv2kT9/fiIiIkIXoMlyrAfZZFdbtmxh9uzZDBw4kM2bN1OyZEn69u3LDTfcQIkSJVK8vtOnT7N27Vr++uuveMnzmjVrOHPmDACRkZFceeWV8Xqbr776akqXLm1teTbnry22BNkYz9q1a2ncuDFHjx5l9uzZVKtW7bxl5syZw+23307dunWZNm0aefLkCUOkJiuwBNlkd3v27OHo0aPkzp2bQoUKBX39J06cYNWqVeeVaqxfv5643CcmJoby5cvHq2+++uqrueyyy8iRwwb6yg4sQTYmAOvXr6dx48b8+++/zJ49m9jYWN544w1efPFFli9fTsuWLSlevDgbN26kXr16zJgxg8mTJ7N8+XIGDRrEG2+8wZEjR+jXrx/9+/enUKFCdO/eHREJ91szGYwlyMaEx9GjR1mxYsV5pRq+I2zkyZOHChUqnHdyYPHixa09z2IsQTYmQBs3bqRx48YcOHCAM2fO8O+//1KkSBH27t1LpUqVmDVrFnPnzuWee+6hWLFiZxvVUqVKsXHjxvPud+vWjSFDhlhvhInHEmRjMpaDBw/y999/n9fjvGPHjrPL5M+f/7yk+eqrr+biiy8OY+QmLewkPWMCVKpUKebPn0+TJk2IiYnhtddeo127dtSoUYOZM2dSoEAB7rzzTqKjo7nrrrto27YtdevWpWvXrvTo0YMCBQrQv39/Xn75ZXbu3MmQIUM4ePAgI0eOJDIy/ldOVZPtjQhkGWOMMWmTP39+6tatS926deNN37t373lJ85QpUxg+fPjZZQoVKnRefbON4Zy5WQ+yMX6cOHGCHDlyEBUVxdGjR4mJiTnvZI7Dhw+TJ08eRITDhw+TN2/es9Pz5s2LqjJgwACeffZZbr31ViZOnHh2mS+//JJ27drRsWNHBg4ceF4Pc2xsLE899RQjRoxgzJgx3HbbbaF54yYkrAfZmMxLVdm5c+fZhNk3ef7333/PLlesWLHzepttDOeMxUosjAmjd999l65du1K5cmWmT5/O1KlTefzxx7n44ovZsWMHLVu25MMPPzw7fuexY8do3749kyZN4pJLLmH37t288cYbPProo2F+JyZYUpogi8jNwFAgAhipqi8nmN8IeAOoBNytqlMCWa+1xcYEj6ryzz//xEuYkxrD2Td5Ll++vI3hHAZpKrFIr4bZmOzioYceomTJkrRu3Zry5ctz6NAhmjdvzoQJExg+fDg9e/bkn3/+4YsvvuD06dO0aNGCxYsX8/LLL9O1a1fuvfdeunXrxpo1a3j99dfPK9UIhUWLFvH777/zwAMP8MMPP7B9+3Zat27NjBkzALj11lvPLhsbG8vo0aOpUqUKNWqEvZM00xORCOBt4AbgH2ChiExT1b99FtsMtAN6hT5CYwy4K7aWKFGCEiVKxBvDOTY2lg0bNpzX45zUGM5xf20M5zBR1SRvuKR4HXAFEA38DlRIsEwpXHI8DmiV3DpVlerVq6sx2c3SpUu1XLly2qtXLz19+vTZ6Z999pnmzp1bixcvrkWLFtW8efPqF198cXb+6dOntXv37gpo48aNddeuXXrmzBmdPXu2Hj58OF1i/fXXX/Wff/7R2NhYfe+99zQqKkoBrVmzpubIkUMBrVOnjgIKaPfu3fXUqVO6f/9+bdasmQIaFRWl7733nsbGxqZLjJkZsEgDaCvdotQFZvk87gv09bPsmEDbYbW22JiwOnXqlK5YsUI/+eQTfe6557RVq1Zavnx5jYiIONu2RkZGaoUKFfSuu+7S559/XqdOnaorV67UU6dOhTv8LMFfWxxIN1QtYK2qrgcQkUlAc+Bsz4WqbvTmxaY8RTcm+6hSpQorVqw4b3qLFi346aefaN68OSLCrFmz+M9//nN2fkREBK+//jqVK1emS5cuVK9enYoVK/L1119Trlw5pkyZQsWKFdm5cyeRkZFcdNFFKYpLVVm1ahVXXXUVp0+f5qmnnuLVV1+lYMGCXHvttXz66afcfPPNNG7cmKeeeoqWLVtStmxZXnrpJbp06UJkZCRDhgxh8eLFbNu2jY0bN/Laa6/xzTff0KVLFxYuXMiwYcPImTNnmrdhNlUc2OLz+B+gdmpXJiKdgE4AJUuWTFtkxphUi4yMpFy5cpQrV45WrVqdnZ7YGM6LFy/mk08+iTeGc7ly5c47OdDGcA6SxLJmjd8b0QpXVhH3uC0wzM+yY0ii5wLXIC8CFpUsWTIU/xgYk6kcO3ZMjx07luQyS5Ys0VKlSmlkZKT27t1bL7nkEs2VK5f26tVL8+XLpwULFtTPPvtMVVXPnDmju3btOm8dx48f13379qmq6s6dO/WWW25RQFu2bKn16tVTQDt06KCVKlVSQJ955pmzPd4HDhw42yN84MCBs+scN26c5syZU4sWLaoLFixQVdfz/fTTTyuglStX1uXLl6uq6tGjR/XgwYNp21iZHCnrQQ5aO5zwZj3IxmQeR44c0UWLFumYMWO0d+/e2rRpUy1ZsuTZ3mZA8+TJozVr1tR27drpq6++ql999ZVu2bLFjuT54a8tDlvDbI2yMal38OBBXbdunaqqbt++Xa+99loFtG7dulqtWjUFtGPHjtqoUSPNkSOH9u3bV48fP66qqgsWLNAyZcpovnz59Nlnn9VLLrlEY2Ji9P7779fIyEjNmzevTpo0SVVdwr5y5cqA49q0aZPu3bv3vOnTp0/XQoUKac6cObVfv35aokQJvfDCC3XixInnLXvmzBnds2dPajZLppLCBNlKLIwxfh08eFB//vlnHTFihD722GN6/fXXa5EiReIlzvnz59d69eppp06ddOjQofrtt9/qzp07wx162KUlQU6XhtkaZWOC5/Tp0zpv3jw9efKknjhxQnv37q2A5suXT5s3b66AVqpUSR999FHNkSOHlipVSuvXr6+AVqxYUf/44w9VVV2+fLlu2rQpXWLctm2b3nDDDQpo2bJltVatWgroXXfdpbt371ZV1ZUrV2qDBg00IiJCn3jiCT169Gi6xJIRpDBBjgTWA5dz7lyQin6WtQTZGKOqqnv27NHvvvtO33nnHX344Ye1UaNGWrBgwXiJc6FChfTaa6/VRx55RN999139/vvvE+3oyKr8tcXJDvMmIpHAauA6YCuwELhHVZcnsuwYYLoGMIqFDS1kTPpavHgxF198MSVKlGD69Ok8+OCD7NixgwcffJDXXnuN3LlzM2/ePOrXrx+yoYViY2OZN28ederUISYmhldeeYX+/ftToEAB7rrrLkaOHEmuXLlo0qQJn376KWXLlmXEiBFcc801IYkvlFIxzNstuNGCIoDRqvqiiLyAa9yniUhN4DPgQuA4sENVKya3XmuLjcleVOOP4ew7sobvGM5FixaNd9GTrDqGc5rGQU6PhtkaZWNCa//+/WzYsIFq1aqFO5R4/vzzTx588EF+/fVXWrVqxVtvvUWRIkX49ttvefDBB9mwYQN33303gwYNylInlNmFQowxGYnq+WM4L1++nOXLl583hnPCKwZm5jGc7UIhxpgM68yZM6xdu5arrroq3vQjR44wePBgBg8ejIjQs2dPevbsSYECBcITaBBZgmyMyQwSjuEc93flypVnx3AWEUqXLn3eiBqZYQxnS5CNMZnWpk2beOKJJ/j444/Jnz8/3bt357HHHsvUibIlyMaYzOz06dOsXbv2vIufrF69mjNnzgBuGLsrr7zyvIuflC5dOmgXvNqzZw9HjhwhT548FCpUKMXPtwTZGJPpLVu2jOeff57PP/+cvHnz8sADD/Doo49StmzZVK9TVVm0aBFLlizhtttuo1ixYkGM2D9LkI0xWdGJEydYvXr1efXN69evjzuRONExnCtWrEipUqUCHsN5y5YtzJ49m5deeonNmzdTsmRJnnrqKW644QZKlCgRcLyWIBtjsoylS5cyZMgQJk2axOnTp7n++utp27Ytd9xxB3nz5j273OrVq/n999+JiIigTp068ZLfPXv2MHnyZEaMGMGyZcsAd0GWZs2aUblyZWbMmEG5cuVo27Yt119/fdAv720JsjEmOzl69CgrVqw4r8d58+bNZ5fJnTs3FSpUOO/kwOLFiyMiZ5fbsmUL7dq1Y+7cuee9TpMmTRgzZkzASbIlyMaYLGfHjh28//77jB07lg0bNpA7d26aNWtGmTJl+PLLL/nrr7/OLisi1K1blyZNmvDTTz8xf/58YmNjqVKlCp06daJevXpMnDiRDz74gF27dlG7dm1Wr17N/v37ufjii7ntttto1qwZ119/fVDO4rYE2Rhj4NChQ/z999/n9Tjv2LHj7DL58+enYsWKZxPmLVu28Oqrr/pd56hRo2jfvn1Ar28JsjEmy1JVfvrpJ8aPH8/nn3/Ozp07adCgAa1ateKaa67h5MmTfP3110ydOpXff/+dcuXK0bJlS1q1akXlypXj9UycPHmSgwcPUrhwYU6cOMHMmTOZOHEis2bN4tChQ0RGRlK9enX++9//0qdPn1THbAmyMcb4t3fv3rOjaPgmz3v37k32uWXKlOHnn38OqCbZEmRjTLYQGxvLkSNH/PbyHjp0iAsuuCDF6z116hQ//fQTX3/9NT/++CNXXXUVI0eOTHWcliAbY0zKxJ0zUrdu3bMnAiYmOjqaNWvWBDQ0qL+2OLhFdcYYE2Y5cuRIsgQiNckxQFRUFNdcc83Zi5aEq3PBGGOyKxHh8ssvp1SpUqxbt87vciVLliR37txpeq3AThU0xhgTj29ZhjHGmNAoVKgQTz31VJLL9O3bN1VDvvmyBNkYY4wxxmQaN9xwA02aNEl0XpMmTbjhhhvS/BqWIBtjjDHGmEyjRIkSjBkzhlGjRlGmTBmio6MpU6YMo0aNStEQb0mxGmRjjDHGGJOplChRgvbt23P77bdz9OhRcufOneayCl+WIBtjjDHGmEwpmEmxr7AN8yYiu4FNqXx6IWBPEMNJK4sneRktJosnaRktHsh4MaU1nstUtXCwgkmtNLTFGe3zMJmT7UcmGNKyHyXaFoctQU4LEVmUEcYPjWPxJC+jxWTxJC2jxQMZL6aMFk+oZff3b4LD9iMTDOmxH9lJesYYY4wxxviwBNkYY4wxxhgfmTVBHh7uABKweJKX0WKyeJKW0eKBjBdTRosn1LL7+zfBYfuRCYag70eZsgbZGGOMMcaY9JJZe5CNMcYYY4xJF5YgG2OMMcYY4yNTJcgicrOIrBKRtSLyZBhev4SIzBORv0VkuYg85k1/TkS2isgy73ZLiOPaKCJ/eq+9yJtWUERmi8ga7++FIYrlKp/tsExEDonI46HcRiIyWkR2ichfPtMS3R7ivOntU3+ISLUQxvSKiKz0XvczESngTS8lIsd8ttV7IYrH72ckIn29bbRKRG4KUTwf+8SyUUSWedNDsX38fdfDuh9lFOFui03ml9h33piU8tdWB4WqZoobEAGsA64AooHfgQohjqEoUM27nw9YDVQAngN6hXHbbAQKJZg2GHjSu/8kMChMn9kO4LJQbiOgEVAN+Cu57QHcAnwFCFAH+DWEMd0IRHr3B/nEVMp3uRDGk+hn5O3jvwMxwOXe9zAiveNJMP814NkQbh9/3/Ww7kcZ4ZYR2mK7Zf5bct95u9ktkJu/tjoY685MPci1gLWqul5VTwKTgOahDEBVt6vqEu/+v8AKoHgoY0iB5sBY7/5YoEUYYrgOWKeqqb1iYqqo6vfAvgST/W2P5sA4dX4BCohI0VDEpKrfqOpp7+EvwKXBft2UxJOE5sAkVT2hqhuAtbjvY0jiEREB7gImBvM1k4nH33c9rPtRBhH2tthkfilsg4xJVHrmZZkpQS4ObPF5/A9hTE5FpBRQFfjVm9TVO7Q6OlTlDD4U+EZEFotIJ2/aJaq63bu/A7gkxDEB3E38pCac28jf9sgo+1V7XA9knMtFZKmIfCciDUMYR2KfUbi3UUNgp6qu8ZkWsu2T4Lue0fejUMhO79UYk0kkkpelSWZKkDMMEckLTAUeV9VDwLtAaaAKsB13ODiUGqhqNaAp8IiINPKdqe7YQ0jH8xORaOB24BNvUri30Vnh2B5JEZGngdPABG/SdqCkqlYFegAficgFIQglw3xGCbQh/j9aIds+iXzXz8po+5ExxmRXSbXVqZWZEuStQAmfx5d600JKRKJwH8IEVf0UQFV3quoZVY0FRhDkw8/JUdWt3t9dwGfe6++MO8Tr/d0VyphwyfoSVd3pxRbWbYT/7RHW/UpE2gG3Avd6CRdeKcNe7/5iXL3nlekdSxKfUdi2kYhEAv8FPvaJMyTbJ7HvOhl0Pwqx7PRejTEZnJ+2Os0yU4K8ECgrIpd7vZN3A9NCGYBXCzkKWKGqr/tM9601vAMI2Vm5IpJHRPLF3ced+PUXbtvc7y12P/BFqGLyxOv1C+c28vjbHtOA//NGIagDHPQ5hJ6uRORmoA9wu6oe9ZleWEQivPtXAGWB9SGIx99nNA24W0RiRORyL57f0jsez/XASlX9xyfOdN8+/r7rZMD9KAzC3hYbYwwk2VanXTjPPkzpDXem+Gpcj9HTYXj9BrhDqn8Ay7zbLcCHwJ/e9GlA0RDGdAXuLPLfgeVx2wW4CPgWWAPMAQqGMKY8wF4gv8+0kG0jXGK+HTiFq4/s4G974EYdeNvbp/4EaoQwprW4Ws64fek9b9mW3me5DFgC3BaiePx+RsDT3jZaBTQNRTze9DFAlwTLhmL7+Puuh3U/yig3wtwW2y3z3/x95+1mt5Tc/LXVwVi3XWraGGOMMcYYH5mpxMIYY4wxxph0ZwmyMcYYY4wxPixBNsYYY4wxxoclyMYYY4wxxviwBNkYY4wxxhgfliCbkBGRkSJSIZXPLSUioR47OSyy03s1xmRMItJNRFaIyIRkljvs/Q1LuyUi7URkWKhf12R9keEOwGQfqtox3DEYY4wJyMPA9epzkR5jshPrQTZB513db4aI/C4if4lIa2/6fBGp4d0/LCIvesv8IiKXeNNLe4//FJEBcb0TCdYfISKviMhCEflDRDqnIIaNIlLIu19DROZ7958TkbEi8oOIbBKR/4rIYC+Or71LWcY9f6CILBORRSJSTURmicg6EeniLZNXRL4VkSXe85t700t5PTIjRGS5iHwjIrm8edW9WH8HHgn2Z2KMMYESkfdwF6H6SkS6e+1jL5/5f4lIqRSsr7dPe/28N62UiKwUkQleuzhFRHJ7864TkaVe+zlaRGK86TVF5CevrfxNvKvIAsW8dnqNiAz2lo0QkTFerH+KSPfgbB2TXViCbNLDzcA2Va2sqlcDXyeyTB7gF1WtDHwPPOhNHwoMVdX/4K6ulJgOuEv51gRqAg+KuwRySmNIqDTQBLgdGA/M8+I4BjTzWW6zqlYBfsBd6a0VUAd43pt/HLhDVasBjYHXvMthgrss8tuqWhE4gLsqHMAHwKPe9jDGmLBR1S7ANqCxqg5Jy7pE5EZcu1cLqAJUF5FG3uyrgHdUtTxwCHhYRHLi2tXWXvsbCTzkXdb8Y+Axr528Htc24623NfAfoLWIlPCmFVfVq731fJCW92GyH0uQTXr4E7hBRAaJSENVPZjIMieB6d79xUAp735d4BPv/kd+1n8j8H8isgz4FXf537KpiCGhr1T1lPfcCM4l1X/6xAfuMsxx039V1X9VdTdwQkQK4C47/JKI/IG7HHFx4BLvORtUdZl3fzFQyntOAVX93pv+YQCxGmNMZnCjd1uKuzR8Oc6111tUdYF3fzzussFX4drJ1d70sUAjb/p2VV0IoKqHVPW0t8y3qnpQVY8DfwOXAeuBK0TkLRG5GZeAGxMwS5BN0HkNWzVcAjlARJ5NZLFTeu4652dIWT284Hpbq3i3y1X1mwBjOM25/T5ngvWe8J4bmyC+2ATxnfCZfsJnetxy9wKFgepeT/NOn9fyXT6l79sYY8LBt92E89vOpAgw0Ke9LqOqo7x5mmDZhI8DdV67qqr7gcrAfKALMDKV6zbZlCXIJuhEpBhwVFXHA6/gEtVA/cK5soO7/SwzC3fILa4u+EoRyRNgDBuB6t79lqSP/MAuVT0lIo1xvRl+qeoB4ICINPAm3ZtOcRljTGpsxGtDRaQakLCkLSmzgPYiktd7fnERudibV1JE6nr37wF+BFbhjqyV8aa3Bb7zphcVkZreevKJiN8OBu9ckxyqOhXoR8p+h4yx3iuTLv4DvCIiscAp4KEUPPdxYLyIPI0rcUisNGIkruRhiVfbuxtoEWAMzwOjROR/uJ6F9DAB+FJE/gQWASsDeM4DwGgRUeCb5BY2xpgQmoora1uOK2tbnczyZ6nqNyJSHvjZOxXjMHAfrqd3FfCIiIzGlUa8q6rHReQB4BMvAV4IvKeqJ72Trd/yTm4+hqtD9qc48IGIxHUE9k3B+zUGOXcU2Zjw885iPqaqKiJ3A21UtXm44zLGGBM83igY072TqI3JcKwH2WQ01YFhXs/wAaB9eMMxxhhjTHZjPcjGGGOMMcb4sJP0jDHGGGOM8WEJsjHGGGOMMT4sQTbGGGOMMcaHJcjGGGOMMcb4sATZGGOMMcYYH/8PdgiX6WKyLxAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot runs \n",
    "section_3_11_helpers.compare_runs(batch_cost_hist,minibatch_cost_hist,minibatch_cost_hist_2)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "include_colab_link": true,
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "toc": {
   "colors": {
    "hover_highlight": "#DAA520",
    "navigate_num": "#000000",
    "navigate_text": "#333333",
    "running_highlight": "#FF0000",
    "selected_highlight": "#FFD700",
    "sidebar_border": "#EEEEEE",
    "wrapper_background": "#FFFFFF"
   },
   "moveMenuLeft": true,
   "nav_menu": {
    "height": "141.067px",
    "width": "251.1px"
   },
   "navigate_menu": true,
   "number_sections": true,
   "sideBar": true,
   "threshold": 4,
   "toc_cell": false,
   "toc_section_display": "block",
   "toc_window_display": false,
   "widenNotebook": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
